SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs
| dc.contributor.author | Li, Quan | en_US |
| dc.contributor.author | Liu, Yingjie J. | en_US |
| dc.contributor.author | Chen, Li | en_US |
| dc.contributor.author | Yang, Xingchao C. | en_US |
| dc.contributor.author | Peng, Yi | en_US |
| dc.contributor.author | Yuan, Xiaoru R. | en_US |
| dc.contributor.author | Wijerathne, Maddegedara Lalith Lakshman | en_US |
| dc.contributor.editor | Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana | en_US |
| dc.date.accessioned | 2020-05-24T13:01:50Z | |
| dc.date.available | 2020-05-24T13:01:50Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Despite the significance of tracking human mobility dynamics in a large-scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. Numerous individual movement trajectories, disaster damages of civil engineering, associated heterogeneous data attributes, as well as complex urban environment all obscure disaster evacuation analysis. Although visualization methods have demonstrated promising performance in emergency evacuation analysis, they cannot effectively identify and deliver the major features like speed or density, as well as the resulting evacuation events like congestion or turn-back. In this study, we propose a shot design approach to generate customized and narrative animations to track different evacuation features with different exploration purposes of users. Particularly, an intuitive scene feature graph that identifies the most dominating evacuation events is first constructed based on user-specific regions or their tracking purposes on a certain feature. An optimal camera route, i.e., a storyboard is then calculated based on the previous user-specific regions or features. For different evacuation events along this route, we employ the corresponding shot design to reveal the underlying feature evolution and its correlation with the environment. Several case studies confirm the efficacy of our system. The feedback from experts and users with different backgrounds suggests that our approach indeed helps them better embrace a comprehensive understanding of the earthquake evacuation. | en_US |
| dc.description.number | 3 | |
| dc.description.sectionheaders | Visual Analytics for Problem Solving | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 39 | |
| dc.identifier.doi | 10.1111/cgf.13999 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 523-535 | |
| dc.identifier.uri | https://doi.org/10.1111/cgf.13999 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf13999 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
| dc.rights | Attribution 4.0 International License | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | ] |
| dc.subject | Human centered computing | |
| dc.subject | Visualization | |
| dc.subject | Visualization design and evaluation methods | |
| dc.title | SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs | en_US |